Gut microbial metabolism is linked to variations in circulating non-high density lipoprotein cholesterol.

BACKGROUND: Non-high-density lipoprotein cholesterol (non-HDL-c) was a strong risk factor for incident cardiovascular diseases and proved to be a better target of lipid-lowering therapies. Recently, gut microbiota has been implicated in the regulation of host metabolism. However, its causal role in the variation of non-HDL-c remains unclear. METHODS: Microbial species and metabolic capacities were assessed with fecal metagenomics, and their associations with non-HDL-c were evaluated by Spearman correlation, followed by LASSO and linear regression adjusted for established cardiovascular risk factors. Moreover, integrative analysis with plasma metabolomics were performed to determine the key molecules linking microbial metabolism and variation of non-HDL-c. Furthermore, bi-directional mendelian randomization analysis was performed to determine the potential causal associations of selected species and metabolites with non-HDL-c. FINDINGS: Decreased Eubacterium rectale but increased Clostridium sp CAG_299 were causally linked to a higher level of non-HDL-c. A total of 16 microbial capacities were found to be independently associated with non-HDL-c after correcting for age, sex, demographics, lifestyles and comorbidities, with the strongest association observed for tricarboxylic acid (TCA) cycle. Furthermore, decreased 3-indolepropionic acid and N-methyltryptamine, resulting from suppressed capacities for microbial reductive TCA cycle, functioned as major microbial effectors to the elevation of circulating non-HDL-c. INTERPRETATION: Overall, our findings provided insight into the causal effects of gut microbes on non-HDL-c and uncovered a novel link between non-HDL-c and microbial metabolism, highlighting the possibility of regulating non-HDL-c by microbiota-modifying interventions. FUNDING: A full list of funding bodies can be found in the Sources of funding section.

Enhanced interactions among gut mycobiomes with the deterioration of glycemic control.

BACKGROUND: The gut mycobiome is closely linked to health and disease; however, its role in the progression of type 2 diabetes mellitus (T2DM) remains obscure. Here, a multi-omics approach was employed to explore the role of intestinal fungi in the deterioration of glycemic control. METHODS: 350 participants without hypoglycemic therapies were invited for a standard oral glucose tolerance test to determine their status of glycemic control. The gut mycobiome was identified through internal transcribed spacer sequencing, host genetics were determined by genotyping array, and plasma metabolites were measured with untargeted liquid chromatography mass spectrometry. FINDINGS: The richness of fungi was higher, whereas its dissimilarity was markedly lower, in participants with T2DM. Moreover, the diversity and composition of fungi were closely associated with insulin sensitivity and pancreatic ß-cell functions. With the exacerbation of glycemic control, the co-occurrence network among fungus taxa became increasingly complex, and the complexity of the interaction network was inversely associated with insulin sensitivity. Mendelian randomization analysis further demonstrated that the Archaeorhizomycetes class, Fusarium genus, and Neoascochyta genus were causally linked to impaired glucose metabolism. Furthermore, integrative analysis with metabolomics showed that increased 4-hydroxy-2-oxoglutaric acid, ketoleucine, lysophosphatidylcholine (20:3/0:0), and N-lactoyl-phenylalanine, but decreased lysophosphatidylcholine (O-18:2), functioned as key molecules linking the adverse effect of Fusarium genus on insulin sensitivity. CONCLUSIONS: Our study uncovers a strong association between disturbance in gut fungi and the progression of T2DM and highlights the potential of targeting the gut mycobiome for the management of T2DM. FUNDINGS: This study was supported by MOST and NSFC of China.

Sleep Factors in Relation to Metabolic Dysfunction-Associated Fatty Liver Disease in Middle-Aged and Elderly Chinese.

CONTEXT: Accumulating evidence implies that sleep disturbance is involved in metabolic disorders. OBJECTIVE: We comprehensively evaluated the association between various dimensions of sleep behaviors and the risk for metabolic dysfunction-associated fatty liver disease (MAFLD). METHODS: In this cross-sectional study of 5011 participants with self-reported sleep behaviors and radiologically diagnosed MAFLD, a comprehensive healthy sleep score was generated to evaluate the associations between sleep behaviors and MAFLD risk using multivariate logistic regression adjusting for demographics, lifestyles, medication, and metabolic comorbidities. Furthermore, mediation analysis was utilized to assess the extent to which obesity explains the effect of sleep quality on MAFLD risk. RESULTS: Late bedtime, snoring, and daytime napping for over 30 minutes significantly associated with an increased risk of MAFLD, with odds ratios (OR) of 1.37 (95% CI 1.10, 1.70), 1.59 (95% CI 1.33, 1.91), and 1.17 (95% CI 1.02, 1.35), respectively, after full adjustments including obesity. Participants with disturbance in nighttime sleep and prolonged daytime napping showed the highest risk for MAFLD (OR 2.38, 95% CI 1.73, 3.27). Each additional increase of healthy sleep score was associated with a 16% reduction in MAFLD risk. Further stratified analysis revealed that people with a sedentary lifestyle and central obesity experienced more prominent adverse effects from poor sleep quality than others. Moreover, obesity accounted for only 20.77% of the total effect of sleep quality on MAFLD risk. CONCLUSIONS: Sleep behaviors, both cumulatively and individually, are associated with MAFLD risk. Public health awareness and strategies should be encouraged to curb MAFLD.

Prevalence and risk factors of metabolic associated fatty liver disease in the contemporary South China population.

BACKGROUND: As a newly proposed diagnosis, data on the prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) is rare. We aimed to assess the prevalence and risk factors of MAFLD using new definition in the contemporary South China population. METHODS: In this population based, cross sectional study, a total of 5377 participants aged 30-79 years old were recruited from the South China between 2018 and 2019. MAFLD was diagnosed in subjects who have both hepatic steatosis and metabolic disorders according to the newly international expert consensus. The total prevalence of MAFLD and prevalence by sex and age was estimated. Demographic characteristics, history of disease, and lifestyle were recorded by participants on a questionnaire. Abdominal ultrasonography was performed and evaluated by experienced sonographers. Multivariable logistic regression was used to calculate the odds ratios (ORs) of MAFLD. RESULTS: Overall prevalence of MAFLD was 29.2% (95% confidence interval [CI] 28.0% to 30.5%). Prevalence was higher in women (31.7%) than in men (25.5%; p < 0.001 for sex difference) and in subjects aged 50 years or older (30.7%) than in those aged 30-49 years (19.8%; p < 0.001 for age difference). In participants diagnosed with MAFLD, the prevalence of overweight/obesity was up to 90.5%, type 2 diabetes (T2DM) and metabolic dysregulation were 25.0% and 62.2%, respectively. Risk factors for MAFLD included overweight/obesity (OR = 4.67; 95% CI, 3.76-5.83), T2DM (OR = 2.41, 95% CI, 1.68-3.47), hypertriglyceridemia (OR = 2.42, 95% CI, 2.03-2.87), high school education (OR = 1.50, 95% CI, 1.23-1.82), high income (OR = 1.22, 95% CI, 1.05-1.42). A lower risk of MAFLD was associated with high physical activity equivalent (OR = 0.71, 95% CI, 0.60-0.85). A U-shaped association of frequency of soups and ORs of MAFLD was found, the adjusted ORs (95% CI) of lower and higher frequency of soups were 1.58 (1.32-1.89) and 1.36 (1.13-1.63), respectively. CONCLUSIONS: Our results showed a high prevalence of MAFLD in the general adult population in South China. Obesity has the greatest impact on MAFLD, physical activity and moderate consumption of soups might be the potential protective factors of MAFLD.

Extracellular Superoxide Dismutase Is Associated With Left Ventricular Geometry and Heart Failure in Patients With Cardiovascular Disease.

Background Extracellular superoxide dismutase (Ec-SOD) is a major scavenger of reactive oxygen species. However, its relationships with abnormal left ventricular (LV) geometry patterns and heart failure (HF) are still unknown in patients with cardiovascular disease. Methods and Results A cross-sectional study was carried out to evaluate the association of serum Ec-SOD activity with LV geometry, as well as HF in 1047 patients with cardiovascular disease. All participants underwent standard echocardiography examination and measurement of serum Ec-SOD activity. Overall, we found a significantly decreased trend of serum Ec-SOD activity from subjects with normal geometry (147.96±15.94 U/mL), subjects with abnormal LV geometry without HF (140.19±20.12 U/mL), and subjects with abnormal LV geometry and overt HF (129.32±17.92 U/mL) after adjustment for potential confounders (P for trend <0.001). The downward trends remained significant in the concentric hypertrophy and eccentric hypertrophy groups after stratification by different LV geometry patterns. Multinomial logistic regression analysis showed that each 10 U/mL increase in serum Ec-SOD activity was associated with a 16.5% decrease in the odds of concentric remodeling without HF (odds ratio [OR], 0.835; 95% CI, 0.736-0.948), a 40.4% decrease in the odds of concentric hypertrophy with HF (OR, 0.596; 95% CI, 0.486-0.730), a 16.1% decrease in the odds of eccentric hypertrophy without HF (OR, 0.839; 95% CI, 0.729-0.965) and a 34.0% decrease in the odds of eccentric hypertrophy with HF (OR, 0.660; 95% CI, 0.565-0.772). Conclusions Serum Ec-SOD activity was independently associated with abnormal LV geometry patterns with and without overt HF. Our results indicate that Ec-SOD might be a potential link between LV structure remodeling and the development of subsequent HF in patients with cardiovascular disease. Registration URL: https://www.clinicaltrials.gov; Unique identifier NCT03351907.